DocumentCode :
49398
Title :
Microwave-Based Stroke Diagnosis Making Global Prehospital Thrombolytic Treatment Possible
Author :
Persson, Mats ; Fhager, Andreas ; Trefna, H.D. ; Yinan Yu ; McKelvey, Tomas ; Pegenius, Goran ; Karlsson, Jan-Erik ; Elam, Mikael
Author_Institution :
Dept. of Signals & Syst., Chalmers Univ. of Technol., Goteborg, Sweden
Volume :
61
Issue :
11
fYear :
2014
fDate :
Nov. 2014
Firstpage :
2806
Lastpage :
2817
Abstract :
Here, we present two different brain diagnostic devices based on microwave technology and the associated two first proof-of-principle measurements that show that the systems can differentiate hemorrhagic from ischemic stroke in acute stroke patients, as well as differentiate hemorrhagic patients from healthy volunteers. The system was based on microwave scattering measurements with an antenna system worn on the head. Measurement data were analyzed with a machine-learning algorithm that is based on training using data from patients with a known condition. Computer tomography images were used as reference. The detection methodology was evaluated with the leave-one-out validation method combined with a Monte Carlo-based bootstrap step. The clinical motivation for this project is that ischemic stroke patients may receive acute thrombolytic treatment at hospitals, dramatically reducing or abolishing symptoms. A microwave system is suitable for prehospital use, and therefore has the potential to allow significantly earlier diagnosis and treatment than today.
Keywords :
Monte Carlo methods; biomedical equipment; brain; computerised tomography; learning (artificial intelligence); medical disorders; medical image processing; microwave imaging; neurophysiology; patient treatment; Monte Carlo-based bootstrap step; acute stroke patients; acute thrombolytic treatment; antenna system; brain diagnostic devices; computer tomography imaging; detection methodology; global prehospital thrombolytic treatment; healthy volunteers; hemorrhagic patients; ischemic stroke patients; leave-one-out validation method; machine-learning algorithm; measurement data; microwave scattering measurements; microwave technology; microwave-based stroke diagnosis; proof-of-principle measurements; Antenna measurements; Antennas; Biomedical measurement; Frequency measurement; Hemorrhaging; Microwave measurement; Microwave theory and techniques; Microwave system; stroke diagnostics; subspace distance classification;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2014.2330554
Filename :
6832574
Link To Document :
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